Instructions to use Bictole/NLP_DEEP_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bictole/NLP_DEEP_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Bictole/NLP_DEEP_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Bictole/NLP_DEEP_2") model = AutoModelForSequenceClassification.from_pretrained("Bictole/NLP_DEEP_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4e18d4e49460df8ceab907c99945951894284d7e4b13d1a1673d207e65eb2d61
- Size of remote file:
- 268 MB
- SHA256:
- 993cba35b67240cdf6d0df13b75be8f3a50844136bb92983ac41ab608e90796e
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